Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/cocorof/geny-executor/verifynpx skills add CocoRoF/geny-executor --skill verifygit clone --depth 1 https://github.com/CocoRoF/geny-executorWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00023 | $0.00806 |
| Opus 5 | $0.00012 | $0.00403 |
| Sonnet 5 | $0.00005 | $0.00161 |
| Haiku 4.5 | $0.00002 | $0.00081 |
Grade A, and why
Verify Project Setup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Verify — host + project setup snapshot
The output below is captured at skill execution time. Read it, note any mismatches, then explain to the user what's healthy, what's suspicious, and what to fix next. Do not re-run these commands yourself — the data is already here.
Operating system + shell
- OS: !
uname -s - Kernel: !
uname -r - Architecture: !
uname -m - Shell: !
echo "$SHELL" - Working dir: !
pwd
Runtime versions
for cmd in node npm pnpm bun yarn python python3 pip uv ruff git gh docker make; do
if command -v "$cmd" >/dev/null 2>&1; then
ver="$("$cmd" --version 2>&1 | head -n 1)"
printf " %-8s %s\n" "$cmd" "$ver"
fi
done
Project files (top-level)
- package.json: !
[ -f package.json ] && echo present || echo absent - pyproject.toml: !
[ -f pyproject.toml ] && echo present || echo absent - requirements.txt: !
[ -f requirements.txt ] && echo present || echo absent - Dockerfile: !
[ -f Dockerfile ] && echo present || echo absent - .env.example: !
[ -f .env.example ] && echo present || echo absent - README.md: !
[ -f README.md ] && echo present || echo absent - LICENSE: !
[ -f LICENSE ] && echo present || echo absent
Git state
- Repo root: !
git rev-parse --show-toplevel 2>/dev/null || echo "(not a git repo)" - Branch: !
git rev-parse --abbrev-ref HEAD 2>/dev/null || echo "(not a git repo)" - HEAD: !
git rev-parse --short HEAD 2>/dev/null || echo "(not a git repo)" - Dirty?: !
git diff --quiet 2>/dev/null && git diff --cached --quiet 2>/dev/null && echo clean || echo dirty
Environment hints
- Node version manager: !
command -v fnm >/dev/null && echo "fnm" || (command -v nvm >/dev/null && echo "nvm" || echo "(none detected)") - Python in PATH points to: !
command -v python || command -v python3 || echo "(none)" - Active virtualenv: !
echo "${VIRTUAL_ENV:-(none)}"
How to interpret
Scan the captured output above. Report findings as:
- Healthy — what's present and at a reasonable version.
- Suspicious — anything that's missing-but-expected (e.g. no git repo when one is expected, no package.json in a node project), or a version that's notably old (Node < 18, Python < 3.10, etc.).
- Recommended next steps — at most three concrete actions, in priority order. Skip if everything looks fine.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 76 lines · 23 tokens per session scan A 0a9610e03fbe
Verify Project Setup is a skill published in the GitHub repository CocoRoF/geny-executor (2 stars, last pushed 4d ago), licensed Apache-2.0. It adds 23 tokens to every session and 806 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.
python-feature-lifecycle
Guidance for package and feature lifecycle in the Agent Framework Python codebase, including stage meanings, feature-stage decorators, feature enums, and how to move APIs from one stage to the next.
build-and-test
How to build and test .NET projects in the Agent Framework repository. Use this when verifying or testing changes.
python-development
Coding standards, conventions, and patterns for developing Python code in the Agent Framework repository. Use this when writing or modifying Python source files in the python/ directory.
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
unit-converter
Convert between common units using a multiplication factor. Use when asked to convert miles, kilometers, pounds, or kilograms.